Abstract
Due to technology limitation and environmental influence (i.e., equipment faults, noises, clutter, interferences, and security attacks), the sensor data collected by Cyber-Physical System (CPS) is inherently noisy and may trigger many false alarms. These false or misleading data can lead to wrong decisions. Therefore, data trustworthiness (i.e., the data is free from error, up to date, and originate from a reputable source) is always preferred. However, it often has high cost and challenges to identify fault, noise, cyber-attack, and real-world facts, especially in heterogeneous and complex IoT environment. In this article, we briefly review the current developments and research trend in this research area. We highlighted all the challenges and potential solutions for the trustworthy data collections in CPS and propose a taxonomy for data trustworthiness in CPS. Taxonomy aims to describe different aspects of research in this field. Furthermore, it will help researchers as a reference point for the design of data reliability and data trustworthiness evaluation methods. Based on the observations, future directions are also suggested.
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Acknowledgments
This work was supported in part by the National Natural Science Foundation of China under Grant 61632009 and 61872097, in part by the Guangdong Provincial Natural Science Foundation under Grant 2017A030308006, and in part by the High-Level Talents Program of Higher Education in Guangdong Province under Grant 2016ZJ01.
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Rahman, H.u., Wang, G., Alam Bhuiyan, M.Z., Chen, J. (2019). Trustworthy Data Collection for Cyber Systems: A Taxonomy and Future Directions. In: Wang, G., El Saddik, A., Lai, X., Martinez Perez, G., Choo, KK. (eds) Smart City and Informatization. iSCI 2019. Communications in Computer and Information Science, vol 1122. Springer, Singapore. https://doi.org/10.1007/978-981-15-1301-5_13
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